Implications of increasing demand for freshwater use from the water footprint of irrigated potato production in Alberta.
Bibliographic record
Abstract
Freshwater use has become a major social and environmental concern in the last two decades. This is due to rising food demand, rapid urbanization, industrial development and climate change which are significantly increasing pressure on freshwater resources (Ridoutt and Pfister, 2010, Gheewala et al., 2013). Agriculture is one of the largest users of global freshwater resources, accounting for about 70% of freshwater withdrawals as irrigation (WWAP, 2009). Irrigation accounts for 84% of the total water use in South Saskatchewan River Basin (SSRB) in Alberta (AMEC 2009). Irrigation water use is competing with other demands for freshwater such as household and industrial consumption. A projection of water supply study for the SSRB in Alberta forecasts that water use in the SSRB will increase 53% from the current 1,981,000 dam3 to about 3,040,000 dam3 by 2030 mainly due to expansion of irrigation districts (AMEC 2009). A significant increase in water use will affect a ratio of total fresh water withdrawals to hydrological availability (WTA) leading to a greater water stress index (WSI) in Alberta. The study aims to assess the water footprint of irrigated potato production in Alberta for two scenarios
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".